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2015 | 15 | 1 | 83-100

Article title

The Application of Asymmetric Liquidity Risk Measure in Modelling the Risk of Investment

Title variants

Languages of publication

EN

Abstracts

EN
The article analyses the relationship between investment risk (as measured by the variance of returns or standard deviation of returns) and liquidity risk. The paper presents a method for calculating a new measure of liquidity risk, based on the characteristic line. In addition, it is checked what is the impact of liquidity risk to the volatility of daily returns. To describe this relationship dynamic econometric models were used. It was found that there was an econometric relationship between the proposed measure liquidity risk and the variance of returns.

Publisher

Year

Volume

15

Issue

1

Pages

83-100

Physical description

Dates

published
2015-06-01
received
2014-10-06
accepted
2015-06-30
online
2015-12-30

Contributors

  • Poznań University of Economics Faculty of Informatics and Electronic Economy Department of Econometrics al. Niepodległości 10, 61-875 Poznań, Poland
  • Poznań University of Economics Faculty of Informatics and Electronic Economy al. Niepodległości 10, 61-875 Poznań, Poland

References

  • Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal of Financial Markets, 5: 31-56.[WoS][Crossref]
  • Amihud, Y. & Mendelson, H. (1986). Asset pricing and the bid-ask spread. Journal of Financial Economics, 17: 223-249.[Crossref]
  • Avramov, D., Chordia, T. & Goyal, A. (2006). Liquidity and Autocorrelation in Individual Stock Returns, Journal of Finance, 61 (5): 2365-2394.[Crossref]
  • Battesse, G.E. & Coelli, T.J. (1992). Frontier production functions, technical efficiency and panel data with application to paddy fanners in India. Journal of Productivity Analysis, 3: 153-169.[Crossref]
  • Battesse, G.E. & Coelli, T.J. (1995). A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data. Empirical Economics, 20: 325-332.[Crossref]
  • Battesse, G.E. & CoRRA, G.S. (1977). Estimation of a Production Frontier Model: Witch Application to the Pastoral Zone of Eastern Australia. Australian Journal of Agricultural Economics, 21: 169-179.[Crossref]
  • Engle, R.F. (1982). Autoregressive conditional heteroscedasticity, with estimates of the variance of United Kingdom inflation. Econometrica, 50: 987-1007.[Crossref]
  • Garsztka P. (2012). Konstrukcja portfela papierów wartościowych z uwzględnieniem płynności walorów. In: Matematyka i informatyka na usługach ekonomii : metody, analizy, prognozy. Ed. D. Appenzeller. Poznań: Wydawnictwo Uniwersytetu Ekonomicznego w Poznaniu (UEP), No. 242 (pp. 56-68).
  • Harvey, A.C. (1990). The Econometric Analysis of Time Series. 2nd ed. Hemel Hempstead: Philip Allan.
  • Jacobs, B. & Levy, K. (2013). Leverage Aversion, Efficient Frontiers, and the Efficient Region. The Journal of Portfolio Management, 39 (3): 54-64.[Crossref]
  • Markowitz, H. (1952). Portfolio selection. Journal of Finance, 7: 77-91.
  • Pastor, L. & Stambaught, R. (2003). Liquidity risk and expected stock returns. Journal of Political Economy. 111: 642-685.[WoS]
  • Pla-Santamaria, D. & Bravo, M. (2013). Portfolio optimization based on downside risk: a meansemivariance efficient frontier from Dow Jones blue chips. Annals of Operations Research, 205 (1): 189-201.[WoS]
  • Sharpe, W.F. (1970). Portfolio Theory and Capital Markets. McGraw-Hill, USA.
  • Wolski, R. (2013). Measures of downside risk under conditions of downturn in the real estate market. Real Estate Management and Valuation, 21 (3): 81-87.

Document Type

Publication order reference

Identifiers

YADDA identifier

bwmeta1.element.doi-10_1515_foli-2015-0030
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